{"id":"https://openalex.org/W4372190823","doi":"https://doi.org/10.1109/icassp49357.2023.10095334","title":"Large Covariance Matrix Estimation with Oracle Statistical Rate","display_name":"Large Covariance Matrix Estimation with Oracle Statistical Rate","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372190823","doi":"https://doi.org/10.1109/icassp49357.2023.10095334"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10095334","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095334","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101644949","display_name":"Quanmin Wei","orcid":"https://orcid.org/0000-0001-5108-3270"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Wei","raw_affiliation_strings":["ShanghaiTech University,School of Information Science and Technology,Shanghai,China","School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ShanghaiTech University,School of Information Science and Technology,Shanghai,China","institution_ids":["https://openalex.org/I30809798"]},{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074721617","display_name":"Ziping Zhao","orcid":"https://orcid.org/0000-0002-8668-6263"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziping Zhao","raw_affiliation_strings":["ShanghaiTech University,School of Information Science and Technology,Shanghai,China","School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ShanghaiTech University,School of Information Science and Technology,Shanghai,China","institution_ids":["https://openalex.org/I30809798"]},{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I30809798"],"apc_list":null,"apc_paid":null,"fwci":0.5829,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59278993,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.7058079838752747},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6841750144958496},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.6482985019683838},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.5085450410842896},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.507466733455658},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.48188477754592896},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47398534417152405},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4578262269496918},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.440395712852478},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43028366565704346},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42658424377441406},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.32746729254722595},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2172752320766449}],"concepts":[{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.7058079838752747},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6841750144958496},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.6482985019683838},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.5085450410842896},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.507466733455658},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.48188477754592896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47398534417152405},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4578262269496918},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.440395712852478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43028366565704346},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42658424377441406},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.32746729254722595},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2172752320766449},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10095334","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095334","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320330944","display_name":"Nature","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W216325278","https://openalex.org/W1601795611","https://openalex.org/W1965125844","https://openalex.org/W1972276842","https://openalex.org/W1990512452","https://openalex.org/W1992511687","https://openalex.org/W1995436190","https://openalex.org/W2000769684","https://openalex.org/W2008681993","https://openalex.org/W2017911295","https://openalex.org/W2030161963","https://openalex.org/W2057535756","https://openalex.org/W2074682976","https://openalex.org/W2090852491","https://openalex.org/W2097515331","https://openalex.org/W2098056745","https://openalex.org/W2101631795","https://openalex.org/W2113968881","https://openalex.org/W2135046866","https://openalex.org/W2259656359","https://openalex.org/W2479782352","https://openalex.org/W2508393166","https://openalex.org/W2582533304","https://openalex.org/W2912400541","https://openalex.org/W2964248738","https://openalex.org/W3098306969","https://openalex.org/W3099609308","https://openalex.org/W3103699839","https://openalex.org/W3111439133","https://openalex.org/W4238253035"],"related_works":["https://openalex.org/W2951195517","https://openalex.org/W2257450129","https://openalex.org/W4301884902","https://openalex.org/W3125041749","https://openalex.org/W3002553509","https://openalex.org/W4287901916","https://openalex.org/W3159329005","https://openalex.org/W1988224349","https://openalex.org/W3009379717","https://openalex.org/W4372190823"],"abstract_inverted_index":{"The":[0],"\u2113":[1,22],"<inf":[2,23],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[3,24],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</inf>":[4,25],"penalized":[5],"covariance":[6,16,65,84],"estimator":[7,43,85,129],"has":[8],"been":[9],"widely":[10],"used":[11],"for":[12,90,99],"estimating":[13],"large":[14,63],"sparse":[15,64],"matrices.":[17],"It":[18,71],"was":[19],"recognized":[20],"that":[21,126],"penalty":[26,38],"introduces":[27],"a":[28,33,45,73,118],"non-negligible":[29],"estimation":[30,57],"bias,":[31],"while":[32],"proper":[34],"utilization":[35],"of":[36,49,81,120],"non-convex":[37,69,100],"may":[39],"lead":[40],"to":[41,54,61,76],"an":[42,106],"with":[44],"refined":[46],"statistical":[47,139],"rate":[48,140],"convergence.":[50],"In":[51],"this":[52,104],"paper,":[53],"eliminate":[55],"the":[56,68,78,82,111,127,133,137],"bias":[58],"we":[59],"propose":[60],"estimate":[62],"matrices":[66],"using":[67],"penalty.":[70],"is":[72,114],"challenging":[74],"task":[75],"analyze":[77],"theoretical":[79,145],"properties":[80],"resulting":[83],"because":[86],"popular":[87],"iterative":[88],"algorithms":[89],"convex":[91,121],"optimization":[92],"no":[93],"longer":[94],"have":[95],"global":[96],"convergence":[97],"guarantees":[98],"optimization.":[101],"To":[102],"tackle":[103],"issue,":[105],"efficient":[107],"algorithm":[108,135],"based":[109],"on":[110],"majorization-minimization":[112],"(MM)":[113],"developed":[115],"by":[116,132],"solving":[117],"sequence":[119],"relaxation":[122],"subproblems.":[123],"We":[124],"prove":[125],"proposed":[128],"computed":[130],"exactly":[131],"MM-based":[134],"achieves":[136],"oracle":[138],"under":[141],"weak":[142],"assumptions.":[143],"Our":[144],"findings":[146],"are":[147],"corroborated":[148],"through":[149],"extensive":[150],"numerical":[151],"experiments.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
